Investigation of waste LDPE with Pongamia pinnata seed for sustainable resource recovery: Thermodynamics, Kinetics and artificial neural network modeling for co-pyrolysis potential
Pyrolysis conversion offers the advantages of significant waste reduction and potential energy recovery. This work examined the potential of combining plastic and agricultural wastes as pyrolysis feedstocks. The mixture of waste low-density polyethylene and Pongamia pinnata seeds was analysed using...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2024-06-01
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| Series: | Sustainable Chemistry for the Environment |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2949839224000324 |
| _version_ | 1797220201094184960 |
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| author | Indra Mohan Satya Prakash Pandey Abhisek Sahoo Sachin Kumar |
| author_facet | Indra Mohan Satya Prakash Pandey Abhisek Sahoo Sachin Kumar |
| author_sort | Indra Mohan |
| collection | DOAJ |
| description | Pyrolysis conversion offers the advantages of significant waste reduction and potential energy recovery. This work examined the potential of combining plastic and agricultural wastes as pyrolysis feedstocks. The mixture of waste low-density polyethylene and Pongamia pinnata seeds was analysed using differential and thermogravimetric methods. In addition to the Coats-Redfern (CR) method, Kissinger-Akahira-Sunose (KAS), Flynn-Wall-Ozawa (FWO), Friedman (FRM), and Kissinger (KN) model-free methods were also applied to calculate the kinetic parameters. The apparent activation energy (Ea) calculation demonstrated that the co-pyrolysis conversion required Ea values of 125–154 kJ mol−1. The artificial neural network (ANN) model was considered to validate thermogravimetric data. The R2 values were near unity in training, validation, and testing conditions, with the minimum possible value for mean square error obtained for the considered heating rates. The Pongamia pinnata seeds and waste plastic mixture could surely be utilized to lessen environmental degradation, add value to leftover seeds and waste low-density polyethylene by extracting fuel for transportation and other commercial activities, and produce industrial chemicals, as found through the kinetic modelling, thermodynamic parameters, and ANN modelling. |
| first_indexed | 2024-04-24T12:45:46Z |
| format | Article |
| id | doaj.art-6483e00a2cf94028ba4bc76d6c155020 |
| institution | Directory Open Access Journal |
| issn | 2949-8392 |
| language | English |
| last_indexed | 2024-04-24T12:45:46Z |
| publishDate | 2024-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Sustainable Chemistry for the Environment |
| spelling | doaj.art-6483e00a2cf94028ba4bc76d6c1550202024-04-07T04:37:06ZengElsevierSustainable Chemistry for the Environment2949-83922024-06-016100089Investigation of waste LDPE with Pongamia pinnata seed for sustainable resource recovery: Thermodynamics, Kinetics and artificial neural network modeling for co-pyrolysis potentialIndra Mohan0Satya Prakash Pandey1Abhisek Sahoo2Sachin Kumar3Department of Energy Engineering, Central University of Jharkhand, Ranchi, IndiaDepartment of Energy Engineering, Central University of Jharkhand, Ranchi, IndiaDepartment of Chemical Engineering, Indian Institute of Technology, Delhi, IndiaDepartment of Energy Engineering, Central University of Jharkhand, Ranchi, India; Centre of Excellence – Green and Efficient Energy Technology (CoE-GEET), CUJ, Ranchi, India; Corresponding author at: Department of Energy Engineering, Central University of Jharkhand, Ranchi, India.Pyrolysis conversion offers the advantages of significant waste reduction and potential energy recovery. This work examined the potential of combining plastic and agricultural wastes as pyrolysis feedstocks. The mixture of waste low-density polyethylene and Pongamia pinnata seeds was analysed using differential and thermogravimetric methods. In addition to the Coats-Redfern (CR) method, Kissinger-Akahira-Sunose (KAS), Flynn-Wall-Ozawa (FWO), Friedman (FRM), and Kissinger (KN) model-free methods were also applied to calculate the kinetic parameters. The apparent activation energy (Ea) calculation demonstrated that the co-pyrolysis conversion required Ea values of 125–154 kJ mol−1. The artificial neural network (ANN) model was considered to validate thermogravimetric data. The R2 values were near unity in training, validation, and testing conditions, with the minimum possible value for mean square error obtained for the considered heating rates. The Pongamia pinnata seeds and waste plastic mixture could surely be utilized to lessen environmental degradation, add value to leftover seeds and waste low-density polyethylene by extracting fuel for transportation and other commercial activities, and produce industrial chemicals, as found through the kinetic modelling, thermodynamic parameters, and ANN modelling.http://www.sciencedirect.com/science/article/pii/S2949839224000324Waste LDPEPongamia pinnata seedsCo-pyrolysisKinetic and thermodynamic parametersArtificial neural network |
| spellingShingle | Indra Mohan Satya Prakash Pandey Abhisek Sahoo Sachin Kumar Investigation of waste LDPE with Pongamia pinnata seed for sustainable resource recovery: Thermodynamics, Kinetics and artificial neural network modeling for co-pyrolysis potential Sustainable Chemistry for the Environment Waste LDPE Pongamia pinnata seeds Co-pyrolysis Kinetic and thermodynamic parameters Artificial neural network |
| title | Investigation of waste LDPE with Pongamia pinnata seed for sustainable resource recovery: Thermodynamics, Kinetics and artificial neural network modeling for co-pyrolysis potential |
| title_full | Investigation of waste LDPE with Pongamia pinnata seed for sustainable resource recovery: Thermodynamics, Kinetics and artificial neural network modeling for co-pyrolysis potential |
| title_fullStr | Investigation of waste LDPE with Pongamia pinnata seed for sustainable resource recovery: Thermodynamics, Kinetics and artificial neural network modeling for co-pyrolysis potential |
| title_full_unstemmed | Investigation of waste LDPE with Pongamia pinnata seed for sustainable resource recovery: Thermodynamics, Kinetics and artificial neural network modeling for co-pyrolysis potential |
| title_short | Investigation of waste LDPE with Pongamia pinnata seed for sustainable resource recovery: Thermodynamics, Kinetics and artificial neural network modeling for co-pyrolysis potential |
| title_sort | investigation of waste ldpe with pongamia pinnata seed for sustainable resource recovery thermodynamics kinetics and artificial neural network modeling for co pyrolysis potential |
| topic | Waste LDPE Pongamia pinnata seeds Co-pyrolysis Kinetic and thermodynamic parameters Artificial neural network |
| url | http://www.sciencedirect.com/science/article/pii/S2949839224000324 |
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